Wide-azimuth angle gathers for wave-equation migration

Sava, Paul; Vlad, Ioan

doi:10.1190/1.3560519

Cited by 40 publications

(28 citation statements)

References 39 publications

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“…The source and receiver wavefields used for imaging, W s and W r , are the wavefields indicated by p in equations (1) and (2). Various techniques have been proposed to convert the space-and time-lag extensions into reflection angles Fomel 2003, 2006;Sava and Vlad 2011;Sava and Alkhalifah 2012) thus facilitating amplitude and velocity analysis in complex geologic structures. Various techniques have been proposed to convert the space-and time-lag extensions into reflection angles Fomel 2003, 2006;Sava and Vlad 2011;Sava and Alkhalifah 2012) thus facilitating amplitude and velocity analysis in complex geologic structures.…”

Section: T H E O R Ymentioning

confidence: 99%

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Anisotropy signature in reverse‐time migration extended images

Sava

Alkhalifah

2014

Geophysical Prospecting

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Reverse‐time migration can accurately image complex geologic structures in anisotropic media. Extended images at selected locations in the Earth, i.e., at common‐image‐point gathers, carry rich information to characterize the angle‐dependent illumination and to provide measurements for migration velocity analysis. However, characterizing the anisotropy influence on such extended images is a challenge. Extended common‐image‐point gathers are cheap to evaluate since they sample the image at sparse locations indicated by the presence of strong reflectors. Such gathers are also sensitive to velocity error that manifests itself through moveout as a function of space and time lags. Furthermore, inaccurate anisotropy leaves a distinctive signature in common‐image‐point gathers, which can be used to evaluate anisotropy through techniques similar to the ones used in conventional wavefield tomography. It specifically admits a V‐shaped residual moveout with the slope of the “V” flanks depending on the anisotropic parameter η regardless of the complexity of the velocity model. It reflects the fourth‐order nature of the anisotropy influence on moveout as it manifests itself in this distinct signature in extended images after handling the velocity properly in the imaging process. Synthetic and real data observations support this assertion.

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Section: T H E O R Ymentioning

confidence: 99%

“…Following the discussion by Sava and Vlad (2011), the wavefield at a reflection point can be conceptually decomposed into planar components, each corresponding to a different propagation direction. This shape has a straightforward physical interpretation.…”

Section: T H E O R Ymentioning

confidence: 99%

Anisotropy signature in reverse‐time migration extended images

Sava

Alkhalifah

2014

Geophysical Prospecting

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“…This follows from the fact that conventional seismic imaging is based on the assumption that wavefields originating from a seismic source propagate to and interact with a discontinuity (i.e., the sea surface in this case) as an incident wavefield (or the up-going wavefield) before returning to the sensor(s) as a reflected seismic wavefield (or the down-going wavefield) [25,26]. Therefore, the two wavefields kinematically coincide at the discontinuity.…”

Section: Imaging Conditionmentioning

confidence: 99%

Imaging 3D Sea Surfaces from 3D Dual-Sensor Towed Streamer Data

Orji

Söllner

Gelius

2013

International Journal of Geophysics

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3D realistic sea surface imaging from 3D dual-sensor towed streamer data is presented. The technique is based on separating data acquired by collocated dual-sensors into up-going and down-going wavefields. Subsequently, these wavefields are extrapolated upwards in order to image the sea surface. This approach has previously been demonstrated using 2D data examples. Here, the focus is on 3D data. Controlled 3D data based on the Kirchhoff-Helmholtz algorithm is generated, and the 3D sea surface imaging technique is applied. For coarsely spaced streamers from 3D field data, the technique is applied streamerwise (i.e., 2D wavefield separation, extrapolation, and imaging). In the latter case, the resulting sea surface profiles corresponding to each time frame are interpolated to demonstrate that the main sea surface characteristics are preserved, and artefacts due to 2D processing of 3D data are mainly limited to areas corresponding to large angles of incidence. Time-varying sea surfaces from two different 3D field data are imaged. The data examples were acquired under different weather conditions. The imaged sea surfaces show realistic wave heights, and their spectra suggest plausible speeds and directions.

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“…Using extended images allows to measure the accuracy of the velocity model by analyzing the moveout of the events (Yang & Sava, 2010), and we can perform transformations from the extended to the angle domain (Sava & Fomel, 2006;Sava & Vlad, 2011;Sava & Fomel, 2003). The extended images provide a measurement of the similarity between the source and receiver wavefields along space and time, so we can exploit these images to analyze and better understand the RTM backscattered events.…”

Section: Extended Imaging Conditionmentioning

confidence: 99%

“…Extended images are commonly used to produce angle gathers (Sava & Fomel, 2006;Sava & Vlad, 2011;Sava & Fomel, 2003) and for velocity estimation (Shen & Symes, 2008;Yang et al, 2013;Yang & Sava, 2011b). …”

Section: Extended Imaging Conditionmentioning

confidence: 99%

Understanding the reverse time migration backscattering: noise or signal?

Díaz

Sava

2012

SEG Technical Program Expanded Abstracts 2012

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Reverse time migration (RTM) backscattered events are produced by the cross-correlation between waves reflected from sharp interfaces (e.g. the top of salt bodies). Commonly, these events are seen as a drawback for the RTM method because they obstruct the image of the geologic structure. Many strategies have been developed to filter out the artifacts from the conventional image. However, these events contain information that can be used to analyze kinematic synchronization between source and receiver wavefields reconstructed in the subsurface. Numeric and theoretical analysis indicate the sensitivity of the backscattered energy to velocity accuracy: an accurate velocity model maximizes the backscattered artifacts. The analysis of RTM extended images can be used as a quality control tool and as input to velocity analysis designed to constrain salt models and sediment velocity.The analysis in this thesis suggest that we can use backscattering events along with reflection data to define a joint optimization problem for velocity model building. The gradient required for model optimization suffers from cross-talk, similar to the more conventional RTM images. In order to avoid the cross-talk, I use a directional filter based on Poynting vectors which preserves the components of the wavefield traveling in the same direction.Using backscattered waves for constraining the velocity in the sediment section requires defining the top of salt in advance, which implies a dynamic workflow for model building in salt environments where both sediment velocity and salt interface change iteratively during inversion.

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Wide-azimuth angle gathers for wave-equation migration

Cited by 40 publications

References 39 publications

Anisotropy signature in reverse‐time migration extended images

Anisotropy signature in reverse‐time migration extended images

Imaging 3D Sea Surfaces from 3D Dual-Sensor Towed Streamer Data

Understanding the reverse time migration backscattering: noise or signal?

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